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ILKOM Jurnal Ilmiah
Published by Universitas Muslim Indonesia
ISSN : 20871716     EISSN : 25487779     DOI : -
Core Subject : Science,
Computer Science & IT
ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, including Artificial intelligence, Computer architecture and engineering, Computer performance analysis, Computer graphics and visualization, Computer security and cryptography, Computational science, Computer networks, Concurrent, parallel and distributed systems, Databases, Human-computer interaction, Embedded system, and Software engineering.
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Articles 24 Documents
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Search results for , issue "Vol 12, No 2 (2020)" : 24 Documents clear
Simple Additive Weighting untuk Front-end Framework Terbaik Yusuf, Lestari; Hidayatulloh, Taufik; Nurlaela, Dini; Utami, Lila Dini; Hasan, Fuad Nur
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.593.136-142

Abstract

Web applications that used to run on a desktop in recent years have received huge demand for this area to be more sophisticated and complex, not only that, but users also want web applications to run on mobile devices. Web appearance that is only designed for computer devices will make users difficult when opening a web page display on a different device. By using the CSS framework library, web developers will be greatly helped in making the program more responsive and can also be run on a variety of Open Source both Windows, iOS, and Android. Decision-making system that can determine the best front-end Framework can be an alternative solution for web developers to determine which front-end framework is easier and more convenient to use. Simple Additive Weighting is used to analyze and decide which the best alternative with calculations that take five main criteria in this research that is Preprocessor, Responsive, Browser Support, Easy to Use, and Template. In this study the highest prefects were obtained by Bootstrap 1,000 while for foundation and bulma get a large prefensie s 0.868 and 0.820.
Algoritma K-Nearest Neighbor dengan Euclidean Distance dan Manhattan Distance untuk Klasifikasi Transportasi Bus Dinata, Rozzi Kesuma; Akbar, Hafizal; Hasdyna, Novia
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.539.104-111

Abstract

K-Nearest Neighbor is a data mining algorithm that can be used to classify data. K-Nearest Neighbor works based on the closest distance. This research using the Euclidean and Manhattan distances to calculate the distance of Lhokseumawe-Medan bus transportation. Data that used in this research was obtained from the Organisasi Angkutan Darat Kota Lhokseumawe. The results of the test with k = 3 has obtained the percentage of 44.94% for Precision, 37.06% Recall, and 81.96% Accuracy for the performance of K-NN with Euclidean Distance. Whereas by using Manhattan Distance the result obtained was 45.49% for Precision, 36.39% Recall, and 84.00% Accuracy. The result shown that Manhattan Distance obtained the highest accuracy, with the difference of 2.04% higher than Euclidean Distance. It indicates that Manhattan Distance is more accurate than Euclidean Distance to classify the bus transportation.
Anti-WebShell PHP Backdoor Scanner pada Linux Server Sopaheluwakan, Christian Ronaldo; Chandra, Dian Widiyanto
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.596.143-153

Abstract

Backdoor or commonly also known as web shell is one of the malicious software that hackers use to maintain access systems that they have entered. Relatively few programs like Anti Web-Shell, PHP Backdoor Scanner circulating on the Internet, and can be obtained free of charge to deal with the issues above. But most of these programs have no actual database of signature behavior to deal with PHP backdoor / Shell nowadays. Then comes the contemporary Anti Web-Shell program that can deal with today's backdoor shell. This study uses an experimental method concerning previous similar studies and is implemented directly into the world of cyber security professional industries. By enriching the Regex dictionary signature and String Array Matching the actualized Anti Web-Shell program can detect more backdoor than similar programs that have existed in the past. The results of this study are in the form of a web application software in PHP extension. The application can minimize 100% of false positives and is twice as fast in scanning files because it is more specific in heuristic analysis scan.
Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak Supriyatin, Wahyu
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.541.112-120

Abstract

Computer vision is one of field of image processing. To be able to recognize a shape, it requires the initial stages in image processing, namely as edge detection. The object used in tracking in computer vision is a moving object (video). Edge detection is used to recognize edges of objects and reduce existing noise. Edge detection algorithms used for this research are using Sobel, Prewitt, Robert and Canny. Tests were carried out on three videos taken from the Matlab library. Testing is done using Simulik Matlab tools. The edge and overlay test results show that the Prewitt algorithm has better edge detection results compared to other algorithms. The Prewitt algorithm produces edges whose level of accuracy is smoother and clearer like the original object. The Canny algorithm failed to produce an edge on the video object. The Sobel and Robert algorithm can detect edges, but it is not clear as Prewitt does, because there are some missing edges.
Perbandingan Metode Klasifikasi Support Vector Machine dan Naïve Bayes untuk Analisis Sentimen pada Ulasan Tekstual di Google Play Store Ilmawan, Lutfi Budi; Mude, Muhammad Aliyazid
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.597.154-161

Abstract

In this research, the performance of SVM classification method will be compared with other classification methods, by using the Naïve Bayes classification method. Naïve Bayes classification method is a light classification method and has a high accuracy if applied to the text classification according to some previous studies. The accuracy of the classifier is measured using the K-fold cross validation method whose results will be tabulated in a confusion matrix table, with a value of K = 3. In this study, the data processed are textual reviews of applications in the Indonesian language Google Play Store obtained from previous research. The test results obtained from the 3-fold cross-validation method produce that SVM Classifier has a higher value of accuracy when compared with the accuracy of the Naïve Bayes classifier, the SVM classifier gets an accuracy of 81.46% and Naïve Bayes classifier by 75.41%.
Performa Klasifikasi K-NN dan Cross Validation pada Data Pasien Pengidap Penyakit Jantung Azis, Huzain; Purnawansyah, Purnawansyah; Fattah, Farniwati; Putri, Inggrianti Pratiwi
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.507.81-86

Abstract

Globally, the number one cause of death each year is cardiovascular disease. Cardiovascular disease is a disease caused by impaired function of the heart and blood vessels, such as coronary heart disease, heart failure or heart failure, hypertension and stroke. The purpose of this study was to measure the performance of accuracy, precision, recall and f-measure of the K-NN and Crossvalidation methods on a dataset of cardiovascular patients. The dataset used was 1000 records consisting of 11 attributes (age, gender, height, etc.) cardiovascular and non cardiovascular patient data, the dataset was obtained from the UCI Machine Learning Repository managed by the Hungarian Institute of Cardiology Budapest: Andras Janosi, MD, University Hospital, Zurich, Switzerland. The steps taken are: dividing the simulation ratio of the dataset to 20:80, 50:50 and 80:20, applying crossvalidation (k-fold = 10) and classification using the K-NN method (k = 2 to K = 900). The research results from the simulation of the dataset ratio 50:50 obtained an accuracy value of 82%, 82% precision, 82% recall and 80% f-measure at a value of K = 13, then the research results from the simulation of the dataset ratio 20:80 obtained an accuracy value of 87%, 87% precision, 97% recall and 92% f-measure at the value of K = 3, and the results of research from the simulation of the dataset ratio 80:20 obtained an accuracy value of 91%, 92% precision, 60% recall and 72% f-measure at the value K = 5.
Algoritma K-Means untuk Pengelompokan Topik Skripsi Mahasiswa Muttaqin, Muhammad Rafi; Defriani, Meriska
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.542.121-129

Abstract

In helping to develop technology in the field of education as well as bringing about a major change in competitiveness between individuals and groups, to be able to do so requires sufficient information and data to be analyzed further. In this case STT Wastukancana Purwakarta is under the auspices of Bunga Bangsa Foundation, seeing that STT Wastukancana Purwakarta students have several obstacles in their final project, one of which is difficult in determining the topic of the thesis title to be made so that sometimes the topic of the thesis title taken is not in accordance with their abilities each student. This problem can be overcome by applying the clustering method. The analytical method used is Knowledge Discovery in Database (KDD). The method of grouping students uses the clustering method and the K-Means algorithm as a clustering calculation where the Clustering aims to divide students into clusters based on grades obtained from semester 1 to 7, so as to produce student recommendations in taking thesis topics. The tool used to implement the algorithm is Rapidminer. The results of this study are grouping students according to their expertise, which is obtained based on the cluster that has the highest score and is dominated by the most subjects according to the subjects that have been grouped by each expertise. So, the results of this cluster are used as a reference for students to take the thesis title topic.
Prototipe Alat Pengusir Burung pada Gedung Berbasis Internet of Things menggunakan Sensor RCWL Khumaidi, Ali
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.602.162-167

Abstract

Sound disturbance and bird droppings in buildings are a problem for building managers. Bird droppings are quite difficult to remove and cause damage to the walls and aesthetics, especially the trend in the use of building roofs as a rooftop for productive activities. This study proposes the use of RCWL motion sensors for motion detection and the resulting output is the sound of eagles from speakers and ultrasonic speakers. The tool was developed based on internet of things using an arduino nano ATMega 328 microcontroller, connection and data transmission using SIM800L and GSM modules and power supply using a solar panel power bank. The test results show that the RCWL motion sensor is quite optimal in the detection of more than or equal to 3 birds. Sound output and the resulting waves are able to prevent birds from alighting and nesting.
Monitoring dan Evaluasi Kinerja Karyawan menggunakan Algoritma Simple Additive Weighting dan Hungarian Gunawan, Wawan; Firmansyah, Muhammad Riski
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.519.87-95

Abstract

Monitoring and evaluating the performance of  employees of PT Akulaku Silvrr Indonesia still use microsoft excel application online,   which has some weaknesses, which is an obstacle in monitoring is that  adalah it is unable to give specific job orders    and can not provide due date information,whereas  in determining the provision of salary increase and employee benefits is done randomly and only based on the last education. Tohelp the company succeed in achieving its goals, a system can be needed that can help in making decisions on a large or small scale. The  use of Simple Additive Weighting  (SAW) method can be used to determine pay raises and incentivize precisely and accurately  based on the specified criteria, while hungarian method is used to determine who will do the job at a difficult, easy and moderate level. So the rating for the salary increase for the support team is Andi Ansyah, Hangga Bagus, Chikal Aviv and Ray Awaludin. Determining the next task can be determined that Andi Ansyah can do the job easily and difficultly, Hangga Bagus can do the job easily and moderately, Chikal Aviv can do a medium and difficult job. While Ray Awaludin does not have the highest value for each job, so it is necessary to be given training.
Deteksi Diabetik Retinopati menggunakan Regresi Logistik Tyasnurita, Raras; Pamungkas, Adhi Yoga Muris
ILKOM Jurnal Ilmiah Vol 12, No 2 (2020)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v12i2.578.130-135

Abstract

Retinopathy diabetic is a disease caused by diabetes mellitus complications that can cause damage to the retina of the eye. It has a direct impact on the disruption of the vision of the patient. Detecting this disease is very important to prevent total blindness on diabetes mellitus patients. One method to do the detection is by using machine learning. This research uses feature extraction data from an image that contains signs of retinopathy diabetic or not. In this research, we focus on retinopathy diabetic classification. We applied logistic regression algorithm for classification. There is four training condition in a machine learning model: using the default parameter, feature standardization, feature selection, and hyper-parameter tuning. The model used a regularization control (C) value of 11.288, iterations 200, and a regularization penalty (l1). The experimental results show that this proposed model with full features produced 80,17% accuracy in data validation.

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